These documents and this posting are a draft and their purpose is to gather information. Therefore, the information is subject to change and does not commit or in any way bind the Department or its Governing Board.

Any final version will go through all normal rulemaking channels.

Introduction to Rent Burden Tie-Breaker

At the QAP Roundtable on May 23, 2018, staff proposed possible tie breaker factors for 10 TAC 11.7. One of these proposed tie-breaker factors is as follows:

“Applications proposed to be located in a census tract with the highest rent burden as compared to another Application with the same score.”

If the Department were to employ rent burden as a tie breaker factor, the Department could use the Comprehensive Housing Affordability Strategy (“CHAS”) dataset, published annually by HUD, since it allows staff to identify renters who make 80% Area Median Family Income (“AMFI”) and it specifies the percentage of their rent that goes to housing costs. The current dataset is 2010-2014 data, but the 2011-2015 data should be released soon.

If this data were used as a tie breaker factor, it would probably need to be combined with another factor that accounts for the poverty rates of census tracts.

The data for every census tract in Texas is attached below. Staff has also identified the top 20 census tracts for regions 3 (urban), 6 (urban), 7 (urban), and 11 (urban), as an example of where this tie-breaker incents Developments.

The handout pertaining to tie-breaker factors from the May 23, 2018 roundtable is also attached below.

Technical Details of Data Attachment

The raw data is located in columns A through Column O.

CHAS refers to rent burden as “housing cost burden,” or “HCB.” CHAS places these households within one of two brackets:

Bracket One

those that have more than 30% HCB but less than 50% HCB

Bracket Two

those that have more than 50% HCB, which is often referred to as “Severe Housing Cost Burden.”

CHAS further defines this data by placing households within one of three AMFI groups:

those that earn less than or equal to 30% AMFI;

those that earn greater than 30% but less than or equal to 50% AMFI, and

those that earn greater than 50% but less than or equal to 80% AMFI.

This data is showcased in columns J through O of the excel sheet. The total number of renter households in each census track per the 2010-2014 CHAS data, including those renter households who are not rent burdened and/or who have incomes greater than 80% AMFI, has been included in column I. The TDHCA state service region has been added for each census tract in column H.

Staff has added calculations to columns P, Q, and R in the excel sheet.

Column P counts the total population of renter households who earn less than 80% AMFI and whose housing expenditures exceed 30% of their income.

Column Q calculates that census tracts’ share of the entire HCB population of renters who earn less than 80% AMFI. This figure is expressed as a percentage.

Column R ranks all of the census tracts, with rank “1” being the census tract with the highest share of the above demographic pool and rank “5088” being the census tract(s) with the lowest share of the above demographic pool.

Potential issues to consider include tracts with large student populations that may skew income statistics and also census tracts that tie each other in rank for the share of statewide HCB renters. Ties may not be an issue for several reasons, including that census tracts that tie each other may not be in the same subregion and, second, another tie breaker would then come into play if they were in the same subregion.

You can also use the CDP mapping tool from HUD to get an idea of where housing cost burden ("HCB") is most prevalent in Texas' census tracts. This tool does not filter for households at or below 80% AMFI, but it does closely align with the data we have provided (which only shows cost burden for households at or below that income threshold). To showcase that data, click 'layers' --> 'Community Indicators' --> 'Housing Need' --> 'Affordability' --> 'Housing Cost Burden', and then zoom to various jurisdictions.

I appreciate the objectivity of this criterion and its consistency with the Statute. The QAP language can simply reference the formula that creates Column Q. I don't see needing to layer any other poverty information with it because high poverty is already addressed in the existing undesirable neighborhood characteristic requirements and the UNCR.

Many of the top scoring census tracts have poverty over 20% and could still get done as revitalization deals. My concern is that this tie breaker incentives too much revitalization deals in really urban areas. I do not think any more incentive for really urban deals needs to be in the QAP as there is more than sufficient point advantage for those already. I would like to see 1st quartile sites beat 2nd quartile and 2nd quartile beat 3rd as a tie breaker. That would create an incentive for development in the best census tracts.

sorry for the late response, below are our thoughts on each tie breaker.

(1) Applications proposed to be located in a census tract with the highest rent burden as compared to another Application with the same score.

Instead of looking at the highest rent burden census tracts, we compared the HRB on recent Austin projects (see below) and found that this tie breaker, after applying the QAP scoring, would award the project in lower income/ higher poverty census tracts. This is a very interesting concept, but we aren’t sure this idea in its current form would award the ‘best project’. We think this concept needs to be tweaked before being used as a tie-breaker.

project

census tract

income

poverty

HRB

Cambrian

23.18

Q4

49.8

1645

Travis Flats

21.05

Q4

26.6

865

Chalmers

9.02

Q4

20

440

Waters Park

18.29

Q3-A

4.9

430

Mueller

3.06

Q2

19.2

315

Aria

14.02

Q2

9.9

305

Goodrich

13.04

Q2

5.5

275

(2) Applications with the most Low-Income Units per the requested Housing Credit Allocation, as represented in the Application.

We feel strongly that the rules should do a better job of incentivizing efficient use of tax credits. We generally support this as a tie- breaker but still urge the department to think through a mechanism that caps soft costs or caps tax credit per unit.

(3) Applications proposed to be located the greatest linear distance from the nearest Housing Tax Credit assisted Development. Developments awarded Housing Tax Credits but do not yet have a Land Use Restriction Agreement in place will be considered Housing Tax Credit assisted Developments for purposes of this paragraph according to the property inventory included in the HTC Site Demographic Characteristics Report. The linear measurement will be performed from closest boundary to closest boundary.

We understand that this is a clear and objective way to pick a winner. We aren’t sure that it supports the ‘best project’. It may be worth referring to the top three neighborhood features identified in the tenant survey (see below). Just a thought, what about a tie-breaker for the smallest linear distance to one of these amenities, or smallest cumulative distance to all of the amenities.

I think the use of rent burden as a tiebreaker depends on the priority of the Department. Is the priority to put developments in higher income (and presumably higher opportunity) areas? If so, then using rent burden does not make much sense to me because it puts developments in areas where there is a higher concentration of people with presumably lower incomes because they cannot afford housing. I would be interested to see how many Q1 census tracts have a rent burden compared to Q4 census tracts.

This past year, with the deletion of educational excellence as a scoring item, significant point advantage for urban core, and the ability of cities to designate multiple priority community revitalization developments in one city, there was a significant increase in competitive applications not in high opportunity areas. This is a departure from the trend of the last several years. Is this what the department wants?

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